Ask HN: Is anyone doing anything cool with tiny language models?

I've been using Llama models to identify cookie notices on websites, for the purpose of adding filter rules to block them in EasyList Cookie. Otherwise, this is normally done by, essentially, manual volunteer reporting.

Most cookie notices turn out to be pretty similar, HTML/CSS-wise, and then you can grab their `innerText` and filter out false positives with a small LLM. I've found the 3B models have decent performance on this task, given enough prompt engineering. They do fall apart slightly around edge cases like less common languages or combined cookie notice + age restriction banners. 7B has a negligible false-positive rate without much extra cost. Either way these things are really fast and it's amazing to see reports streaming in during a crawl with no human effort required.

Code is at https://github.com/brave/cookiemonster. You can see the prompt at https://github.com/brave/cookiemonster/blob/main/src/text-cl....

Maybe it could also send automated petitions to the EU to undo cookie consent legislation, and reverse some of the enshitification.

Ha, I'm not sure the EU is prepared to handle the deluge of petitions that would ensue.

On a more serious note, this must be the first time we can quantitatively measure the impact of cookie consent legislation across the web, so maybe there's something to be explored there.

why don't you spam the companies who want your data instead? The sites can simply stop gathering your data, then they will not require to ask for consent ...